1. Technical Field of the Invention
The present invention relates generally to the field of signal detection and, more particularly, to adaptive control of a detection threshold.
2. Description of Related Art
A radar system measures the distance and/or velocity of a target by sensing the effects of the interaction of the target with a beam of continuous or pulsed electromagnetic energy. The radar receiver measures the distance to the target from differences in the time, for example, between the received and transmitted signal. When the radar energy reaches a target, some portion is reflected back at the radar receiver. This is referred to as backscatter. The portion of the energy that is scattered back at the receiver is determined by the radar cross section (RCS) of the target. The backscatter is not normally constant with time, but fluctuates based on small changes in orientation. In 1954, Peter Swerling described two different categories of fluctuation: pulse-to-pulse and scan-to-scan. xe2x80x9cPulse-to-pulsexe2x80x9d described targets and pulse rates where the amplitude of the backscatter from pulse to pulse varied significantly and was uncorrelated from one pulse to the next pulse. xe2x80x9cScan-to-Scanxe2x80x9d described targets and pulse rates where the amplitude of the backscatter from pulse to pulse is correlated and relatively stable, but changes significantly from one scan of the radar to the next scan.
Radar systems must be operable in environments, which limit radar performance. Internal noise of the system as well as undesirable echoes due to rain, land and sea returns, for example, make target discrimination more difficult often overloading the signal processor that is tracking the target of interest. To distinguish the echo resulting from a target from undesired echoes and/or noise, a field of adaptive or mean level detection has developed.
In order to counteract the above-described problem, statistical techniques were developed to compare the power level of a cell of interest with the detection threshold to indicate whether a target is located in the cell of interest with a specific probability of false alarm. Some techniques use a detection threshold that is determined from a known mean level of undesirable echoes and noise. The objective is to provide a constant false-alarm rate while maintaining detection probabilities for known signals of interest.
For digital type radar equipment and passive detection systems, current methods select binary integration thresholds from a estimate of the backscatter fluctuation statistics from one of the four Swerling models. Binary Integration, better known as xe2x80x9cM of N detectionxe2x80x9d, refers to a series of statistical experiments mathematically described by the binomial equation. xe2x80x9cNxe2x80x9d refers to the number of independent trials (samples or pulses) and xe2x80x9cMxe2x80x9d refers to the number of required favorable outcomes (samples or pulse above a threshold) within the xe2x80x9cNxe2x80x9d trials. In current applications a fixed value threshold is used, however, this approach leads to reduced sensitivity and an inability to adapt to dynamic background effects, such as energy fluctuation and scintillation.
Because current methods offer no method to dynamically adapt to the real-time fluctuations, optimal performance is only attained for a few standard fluctuation cases. Therefore, there is a need for a method to detect changes in signal fluctuation, and adapt the detection scheme to maintain a high level of sensitivity within a single system.
The present invention achieves technical advantages as an apparatus, method and system of dynamically estimating a coefficient of variation of the fluctuation of a waveform and an optimal binary detection threshold using the estimated coefficient of variation. Initially, an A/D converter receives an analog waveform signal and converts the signal to digital form, which is fed to a hard thresholding unit. The hard thresholding unit discriminates between a noise signal and a signal-plus-noise signal by comparison with a threshold in which the noise signal is used to estimate a mean noise floor level and the signal-plus-noise is used to estimate a standard deviation. The hard thresholding unit further determines the coefficient of variation based on the ratio of standard deviation to mean. An optimal threshold estimator uses the estimated coefficient of variation, presets for cumulative probability of false alarm and collection time to determine the optimal binary detection threshold.
For a more complete understanding of the present invention, reference is made to the following detailed description taken in conjunction with the accompanying drawings wherein:
FIG. 1 illustrates a method of determining an optimal binary detection threshold in accordance with the present invention;
FIG. 2 illustrates a block diagram of a preferred detection system in accordance with the present invention; and
FIG. 3 show a table of parameters for various Swerling Fluctuation models.